The 2018 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA 2018) has been organized since 2005. It aims to bring together the researchers from the entire spectrum of the multi-disciplinary fields of intelligent systems and establish effective means of communication between them. In particular, it focuses on all aspects of intelligent systems and the related applications, from the points of view of both theory and practice. Apart of the main track it includes work-shops, tutorials, special sessions and plenary talks by invited speakers.

The conference will be hosted in Thessaloniki Greece. Thessaloniki (520 km. north of Athens) is the second largest city of Greece and the most important centre of the area. Built near the sea (at the back of the Thermaïkos Gulf), it is a modern metropolis bearing the marks of its stormy history and its cosmopolitan character, which give it a special beauty and charm. Take a tour in the centre of Thessaloniki and plan to visit its nearby destinations. Also, while being in Thessaloniki it is worth going up to Halkidiki.

Special Sessions

Reasoning-based Intelligent Systems (RIS 2018)

The RIS 2018 Special Session will identify new advances of all kinds of intelligent computing methods and their practical applications, and publish the academic and technical achievement widely. Opportunities will be offered for researchers and practitioners to exchange ideas about all kinds of reasoning-based intelligent systems, not only theoretical developments but also practical applications.

Dynamic Multi-objective Optimization (DMOO 2018)

Cancelled

The main goal of this special session is to emphasize the newest techniques in solving dynamic multi-objective optimization problems and handling the current issues. So the session aims at providing a forum for researchers in the area of DMOO to exchange new ideas and submit their original and unpublished work.

Enabling Blockchain technologies for Intelligent Systems (EnBIS 2018)

Blockchain distributed ledger technology is a new paradigm of architecture that provides decentralised consensus among a large number of otherwise untrusted peers. The integration of such architectures in Intelligent Systems poses many challenges, but also enhances their security, scalability, autonomy and mitigates trust issues. The Special Session on Enabling Blockchain technologies for Intelligent Systems (EnBIS) at the 2018 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA 2018), is devoted to accelerate the adaptation of Blockchain and Intelligent Systems, such as Internet of Things, Automation, Expert Systems, eHealth, Transportation Systems and others. New promising research directions as well as recent advances in this area are highly welcome to this special session.

The provision of large amount of data from various sources (Internet, Social Media, Application Logs, Data Warehouses, Sensors, Mobiles, Open Data, etc.) is now emerging into the collection and processing of “Big Data”. While Big Data notion is adopted by both academic and enterprise communities, there is currently a wide gap between its potential and its realization. Variety, velocity, scale, complexity, interpretation and security problems with Big Data raise challenges at all phases of the pipeline that can extract information and knowledge from it. Thus, there is a natural interest in using these data assets to improve a variety of applications. It is very interesting to explore how researchers utilize intelligent data-driven strategies and discover what disciplines will change because of the advent of data. With the vast amount of data now available, modern businesses are facing the challenges of storage, management, analysis, privacy, visualization, security and data integration.

The focus of this special season is on current technological advances and challenges about the development of intelligent methods and tools in the areas of Big Data, Software Services and Cloud Computing.

Deployment Areas of Dynamic Environments (DADE 2018)

In real world a great majority of processes are time-dependant by nature. Therefore, methodologies of processing data and information in dynamic environments are widely studied. In particular, application areas like for instance in business, medicine, or smart cities are expanding rapidly such that the trend creates the challenge for research community to build new infrastructure aimed at meeting the innovative requirements.

One of the fundamental goals in computational intelligence is to achieve the ability to effective computer-assisted learning from noisy, uncertain and incomplete data in order to adapt to constantly changing environments. Examples of such dynamic environments, which require some well-defined and verified methods and tools, include Internet of Things networks and real-time systems. Substantial changes, concept drift and some newly emerging trends in dynamic environments can have an impact on the increasing number of imprecise predictive methods, the rate of false alarms and consequently it may influence the systems performance and/or security.

The special session aims at presenting novel approaches to learning and adaptation to dynamic environments both from theoretical and practical application-oriented perspective.

Artificial Intelligence (AI) has been applied successfully to many fields such as data analysis, finance, multimedia, signal and image processing, web technologies, robotics, and automations, etc. Machine learning, as a major technology behind AI, is changing the world rapidly by deploying varied algorithms. For example, artificial neural networks, especially those for deep learning, are implemented in real world such as the GPU computations owing to the maturity of high-speed and parallel architecture. The latter is also becoming a promising research field for further explorations. Many researches of machine learning are inspired by the developments of computational intelligence. How machine learning can be contributed to varied applications related to intelligence is the main focus of this special session.

The methodologies of machine learning may include mathematical or statistical foundations, algorithms, architectures, and uncertainty issues. As for applications of machine learning, we look forward to including researches or implementations in varied fields that are emerged to intelligence and automation. For future trends of machine learning, we encourage authors to propose their innovative ideas and concepts. We offer an opportunity for researchers and practitioners to identify new promising research directions as well as to publish recent advances in this area.